García Blas, Francisco JavierRío Astorga, David delGarcía Sánchez, José DanielCarretero Pérez, Jesús2020-02-102020-02-102019-07-042019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 14-17 May 2019, Larnaca, Cyprus, Pp. 631-637978-1-7281-0912-1https://hdl.handle.net/10016/29675Proceeding of: 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), Larnaca, Cyprus, 14-17 May 2019ASPIDE: Exascale programIng models for extreme data processingIn recent years, on-line processing of data streams has been established as a major computing paradigm. This is due mainly to two reasons: first, more and more data are generated in near real-time that need to be processed; the second reason is given by the need of efficient parallel applications. However, the above-mentioned areas expose a tough challenge over traditional data-analysis techniques, which have been forced to evolve to a stream perspective. In this work we present an comparative study of a stream-aware multi-staged application, which has been implemented using GrPPI, a generic and reusable parallel pattern interface for C++ applications. We demonstrate the benefits of using this interface in terms of programability, performance, and scalability.7eng© 2019 IEEE.MRI reconstructionStream parallelismGrppiconference paperInformáticahttps://doi.org/10.1109/CCGRID.2019.00081open access6316372019 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 14-17 May 2019, Larnaca, CyprusCC/0000030283